“…You will learn about data analytics and exploratory data analysis techniques using multiple different data structures with NumPy and Pandas libraries. You will also learn various chart/graph types, customization/configuration, and vectorization techniques. …”

“…Create real-world machine learning solutions using NumPy, pandas, matplotlib, and scikit-learn Key Features Develop a range of healthcare analytics projects using real-world datasets Implement key machine learning algorithms using a range of libraries from the Python ecosystem Accomplish intermediate-to-complex tasks by building smart AI applications using neural network methodologies Book Description Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. …”

“…Use the Python library Snakebite to access HDFS programmatically from within Python applications Write MapReduce jobs in Python with mrjob, the Python MapReduce library Extend Pig Latin with user-defined functions (UDFs) in Python Use the Spark Python API (PySpark) to write Spark programs with Python Learn how to use the Luigi Python workflow scheduler to manage MapReduce jobs and Pig scripts Zachary Radtka, a platform engineer at Miner & Kasch, has extensive experience creating custom analytics that run on petabyte-scale data sets…”

“…The second level will take you through Python IDE (PyCharm), comments, functions, and scope. The third level is about conditions (if) and loops, followed by the fourth level, which is to read/write to a file, use and create Python modules, and run a Python program from the terminal. …”

“…Learn to use Matplotlib, NumPy, Flask, and Android APK files. Learn database handling and build geographical apps. …”

“…Then progress to exploring data analysis and visualization techniques for time series data, ranging from basic to advanced levels, using powerful libraries such as NumPy, Pandas, and Matplotlib. Python will be utilized to assess various aspects of your time series data, such as seasonality, trend, noise, autocorrelation, mean over time, correlation, and stationarity. …”

“…Sie basieren auf Python und den Bibliotheken Scikit-Learn, Pandas, NumPy, TensorFlow und Keras. Nach der Lektüre dieses Buchs hast du einen Überblick über das gesamte Thema und kannst Ansätze einordnen und bewerten. …”

“…This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries--Theano and TensorFlow--and the API for dealing with these called Keras. …”

“…You will work on a random element selector, perform data analysis and data visualization with the help of NumPy, Pandas, and matplotlib. You will also create a trees survey report, user credentials data, and sales data report. …”

“…As you progress, delve into installing key AI libraries like OpenCV and PyTorch. Understand their roles in crafting robust AI solutions and enhance their performance with CUDA support. …”

“…Starting with an introduction to data visualization, this book shows you how to first prepare raw data for visualization using NumPy and pandas operations. As you progress, you'll use plotting techniques, such as comparison and distribution, to identify relationships and similarities between datasets. …”

“…Machine learning and data science for programming beginners using Python with scikit-learn, SciPy, Matplotlib and Pandas About This Video Learn machine learning and data science using Python A practical course designed for beginners who are interested in machine learning using Python In Detail Artificial intelligence, machine learning, and deep learning neural networks are the most used terms in the technology world today. …”

“…Explore data science using Python, statistical techniques, EDA, NumPy, Pandas, Scikit Learn, and Statsmodel libraries and take your first step toward becoming a data scientist or a machine learning engineer. …”

“…Python Tools for Scientists introduces you to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy, matplotlib, and pandas. No prior programming experience is required. …”

“…You need to have an active AWS account in order to perform the sections related to Python and PySpark. For the rest of the course, a free trial Snowflake account should suffice. …”